Managing multiple programming languages in a data science workflow often means jumping from one environment to another—adding friction to already complex processes. This slows down collaboration and innovation among teams. But what if there were a way to remove this friction between environments? Working in a single environment that supports multiple coding languages helps give teams time back for development, rather than managing tools. For example, being able to run Python, R, and SAS tog...
